SoroushVahidi/scidocs huggingface dataset:
Toward understanding characteristics of dedicated short range communications (DSRC) from a perspective of vehicular network engineers
(2010)

IEEE 802.11p-based Dedicated Short Range Communications (DSRC) is considered a promising wireless technology for enhancing transportation safety and improving highway efficiency. Here, using a large set of empirical measurement data taken in a rich variety of realistic driving environments, we attempt to characterize communication properties of DSRC as well as to analyze the causes of communication loss. Specifically, from a perspective of vehicular network engineers, the fundamental characteristic of DSRC communications is Packet Delivery Ratio (PDR). We investigate the impact of both uncontrollable environmental factors and controllable radio parameters on DSRC characteristics. Moreover, we also examine temporal correlation, spatial correlation and symmetric correlation of DSRC characteristics under realistic vehicular environments.
Learning Common Representation from RGB and Depth Images
(2018)

We propose a new deep learning architecture for the tasks of semantic segmentation and depth prediction from RGBD images. We revise the state of art based on the RGB and depth feature fusion, where both modalities are assumed to be available at train and test time. We propose a new architecture where the feature fusion is replaced with a common deep representation. Combined with an encoder-decoder type of the network, the architecture can jointly learn models for semantic segmentation and depth estimation based on their common representation. This representation, inspired by multi-view learning, offers several important advantages, such as using one modality available at test time to reconstruct the missing modality. In the RGB-D case, this enables the cross-modality scenarios, such as using depth data for semantically segmentation and the RGB images for depth estimation. We demonstrate the effectiveness of the proposed network on two publicly available RGB-D datasets. The experimental results show that the proposed method works well in both semantic segmentation and depth estimation tasks.
Brain Activity during Episodic Retrieval of Autobiographical and Laboratory Events: An fMRI Study using a Novel Photo Paradigm
(2004)

Functional neuroimaging studies of episodic memory retrieval generally measure brain activity while participants remember items encountered in the laboratory (controlled laboratory condition) or events from their own life (open autobiographical condition). Differences in activation between these conditions may reflect differences in retrieval processes, memory remoteness, emotional content, retrieval success, self-referential processing, visual/spatial memory, and recollection. To clarify the nature of these differences, a functional MRI study was conducted using a novel photo paradigm, which allows greater control over the autobiographical condition, including a measure of retrieval accuracy. Undergraduate students took photos in specified campus locations (controlled autobiographical condition), viewed in the laboratory similar photos taken by other participants (controlled laboratory condition), and were then scanned while recognizing the two kinds of photos. Both conditions activated a common episodic memory network that included medial temporal and prefrontal regions. Compared with the controlled laboratory condition, the controlled autobiographical condition elicited greater activity in regions associated with self-referential processing (medial prefrontal cortex), visual/ spatial memory (visual and parahippocampal regions), and recollection (hippocampus). The photo paradigm provides a way of investigating the functional neuroanatomy of real-life episodic memory under rigorous experimental control.
Ambient RF Energy-Harvesting Technologies for Self-Sustainable Standalone Wireless Sensor Platforms
(2014)

In this paper, various ambient energy-harvesting technologies (solar, thermal, wireless, and piezoelectric) are reviewed in detail and their applicability in the development of self-sustaining wireless platforms is discussed. Specifically, far-field low-power-density energy-harvesting technology is thoroughly investigated and a benchmarking prototype of an embedded microcontroller-enabled sensor platform has been successfully powered by an ambient ultrahigh-frequency (UHF) digital TV signal (512-566 MHz) where a broadcasting antenna is 6.3 km away from the proposed wireless energy-harvesting device. A high-efficiency dual-band ambient energy harvester at 915 MHz and 2.45 GHz and an energy harvester for on-body application at 460 MHz are also presented to verify the capabilities of ambient UHF/RF energy harvesting as an enabling technology for Internet of Things and smart skins applications.
Advanced Voltage Support and Active Power Flow Control in Grid-Connected Converters Under Unbalanced Conditions
(2018)

Supporting the grid and improving its reliability have recently become major requirements for large distributed generation units. Under most grid faults, the accuracy of the traditional voltage support schemes (VSSs) is dramatically affected due to the existence of the zero-sequence voltage. Also, the traditional VSSs have been used only in the STATCOM applications, where the active power is zero. This paper proposes an advanced VSS in the converter-interfaced units, called zero-sequence compensated voltage support (ZCVS), to accurately regulate the three-phase voltages of the connection point within the pre-set safety limits. The proposed scheme not only compensates the zero-sequence component but also considers the active power injection. Unlike the traditional methods, the proposed VSS is adapted even in resistive distribution systems. The contribution of this paper is, however, ternate. As the second contribution, the limited active power oscillation (LAPO) is proposed to be augmented to the ZCVS. This feature limits the oscillation to a specified value which provides an adjustable dc-link voltage oscillation setting while simultaneously supporting the ac host grid, even under severe unbalanced faults. Third, the maximum active power delivery (MAPD) to the ac grid is also formulated for the ZCVS. The successful results of the proposed support scheme and complementary strategies are verified using selected simulation and experimental test cases.
A critical examination of 3D stackable NAND Flash memory architectures by simulation study of the scaling capability
(2010)

Various 3D NAND Flash array architectures including P-BiCS, TCAT, VSAT, and VG are critically examined in this work by extensive 3D TCAD simulations. All structures have X,Y lateral scaling limitation since the minimal ONO thickness (∼20 nm) and poly channel thickness (∼10nm) can not be scaled further. Among them VG may have the best X-direction scalability to F∼2X nm node, and no penalty of increasing Z layer number since the channel current flows horizontally. We propose a buried-channel junction-free NAND to improve the read current for all 3D NAND arrays and our simulation results well support this structure. For the first time, “Z-interference” in 3D NAND Flash is examined and it indicates a new Z-direction scaling limitation. The present work is of crucial importance in understanding various 3D NAND Flash approaches.
ICIET ’ 14 Image Steganography Method Using Integer Wavelet Transform
(2015)

Digital Steganography explains the art and science of writing hidden messages in such a way that, apart from the sender and intended recipient, no one suspects the existence of the message, a form of security through the state of being unknown. The main two famous schemes used for image steganography are spatial domain embedding and transform domain embedding. The main aim of Wavelet Transform is used to transform original image (cover image) from spatial domain to frequency domain. But here in our proposed work, Integer Wavelet Transform is performed on a gray level cover image and in turn embeds the message bitstream into the LSB's of the integer wavelet coefficients of a the image . The main purpose of the proposed work is to focus on improving embedding capacity and bring down the distortion occurring to the stego image. The refinement of the algorithm plays an important role for accomplishing higher embedding capacity and low distortion rate. The experimental results prove that the assessment metric such as PSNR is improved in a high manner. The experimental results show that the algorithm has a high capacity and a good invisibility.
Business ecosystem as the new approach to complex adaptive business environments
(2004)

This paper discusses the concept of business ecosystem. Business ecosystem is a relatively new concept in the field of business research, and there is still a lot of work to be done to establish it. First the subject is approached by examining a biological ecosystem, especially how biological ecosystems are defined, how they evolve and how they are classified and structured. Second, different analogies of biological ecosystem are reviewed, including industrial ecosystem, economy as an ecosystem, digital business ecosystem and social ecosystem. Third, business ecosystem concept is outlined by discussing views of main contributors and then bringing authors’ own definition out. Fourth, the emerging research field of complexity in social sciences is brought out due to authors’ attitude to consider ecosystems and business ecosystems as complex, adaptive systems. The focal complexity aspects appearing in business ecosystems are presented; they are self-organization, emergence, co-evolution and adaptation. By connecting business ecosystem concept to complexity research, it is possible to bring new insights to changing business environments.
Framing the Salmonidae Family Phylogenetic Portrait: A More Complete Picture from Increased Taxon Sampling
(2012)

Considerable research efforts have focused on elucidating the systematic relationships among salmonid fishes; an understanding of these patterns of relatedness will inform conservation- and fisheries-related issues, as well as provide a framework for investigating evolutionary mechanisms in the group. However, uncertainties persist in current Salmonidae phylogenies due to biological and methodological factors, and a comprehensive phylogeny including most representatives of the family could provide insight into the causes of these difficulties. Here we increase taxon sampling by including nearly all described salmonid species (n = 63) to present a time-calibrated and more complete portrait of Salmonidae using a combination of molecular markers and analytical techniques. This strategy improved resolution by increasing the signal-to-noise ratio and helped discriminate methodological and systematic errors from sources of difficulty associated with biological processes. Our results highlight novel aspects of salmonid evolution. First, we call into question the widely-accepted evolutionary relationships among sub-families and suggest that Thymallinae, rather than Coregoninae, is the sister group to the remainder of Salmonidae. Second, we find that some groups in Salmonidae are older than previously thought and that the mitochondrial rate of molecular divergence varies markedly among genes and clades. We estimate the age of the family to be 59.1 MY (CI: 63.2-58.1 MY) old, which likely corresponds to the timing of whole genome duplication in salmonids. The average, albeit highly variable, mitochondrial rate of molecular divergence was estimated as ~0.31%/MY (CI: 0.27-0.36%/MY). Finally, we suggest that some species require taxonomic revision, including two monotypic genera, Stenodus and Salvethymus. In addition, we resolve some relationships that have been notoriously difficult to discern and present a clearer picture of the evolution of the group. Our findings represent an important contribution to the systematics of Salmonidae, and provide a useful tool for addressing questions related to fundamental and applied evolutionary issues.
Metrics for Polyphonic Sound Event Detection
(2016)

This paper presents and discusses various metrics proposed for evaluation of polyphonic sound event detection systems used in realistic situations where there are typically multiple sound sources active simultaneously. The system output in this case contains overlapping events, marked as multiple sounds detected as being active at the same time. The polyphonic system output requires a suitable procedure for evaluation against a reference. Metrics from neighboring fields such as speech recognition and speaker diarization can be used, but they need to be partially redefined to deal with the overlapping events. We present a review of the most common metrics in the field and the way they are adapted and interpreted in the polyphonic case. We discuss segment-based and event-based definitions of each metric and explain the consequences of instance-based and class-based averaging using a case study. In parallel, we provide a toolbox containing implementations of presented metrics.
Towards Haskell in the cloud
(2011)

We present Cloud Haskell, a domain-specific language for developing programs for a distributed computing environment. Implemented as a shallow embedding in Haskell, it provides a message-passing communication model, inspired by Erlang, without introducing incompatibility with Haskell's established shared-memory concurrency. A key contribution is a method for serializing function closures for transmission across the network. Cloud Haskell has been implemented; we present example code and some preliminary performance measurements.
Aphasia after stroke: type, severity and prognosis. The Copenhagen aphasia study.
(2004)

AIM
To determine the types, severity and evolution of aphasia in unselected, acute stroke patients and evaluate potential predictors for language outcome 1 year after stroke.


METHODS
270 acute stroke patients with aphasia (203 with first-ever strokes) were included consecutively and prospectively from three hospitals in Copenhagen, Denmark, and assessed with the Western Aphasia Battery. The assessment was repeated 1 year after stroke.


RESULTS
The frequencies of the different types of aphasia in acute first-ever stroke were: global 32%, Broca's 12%, isolation 2%, transcortical motor 2%, Wernicke's 16%, transcortical sensory 7%, conduction 5% and anomic 25%. These figures are not substantially different from what has been found in previous studies of more or less selected populations. The type of aphasia always changed to a less severe form during the first year. Nonfluent aphasia could evolve into fluent aphasia (e.g., global to Wernicke's and Broca's to anomic), whereas a fluent aphasia never evolved into a nonfluent aphasia. One year after stroke, the following frequencies were found: global 7%, Broca's 13%, isolation 0%, transcortical motor 1%, Wernicke's 5%, transcortical sensory 0%, conduction 6% and anomic 29%. The distribution of aphasia types in acute and chronic aphasia is, thus, quite different. The outcome for language function was predicted by initial severity of the aphasia and by the initial stroke severity (assessed by the Scandinavian Stroke Scale), but not by age, sex or type of aphasia. Thus, a scoring of general stroke severity helps to improve the accuracy of the prognosis for the language function. One year after stroke, fluent aphasics were older than nonfluent aphasics, whereas such a difference was not found in the acute phase.
Measuring semantic similarity between Gene Ontology terms
(2007)

Many bioinformatics applications would benefit from comparing proteins based on their biological role rather than their sequence. This manuscript adds two new contributions. First, a study of the correlation between Gene Ontology (GO) terms and family similarity demonstrates that protein families constitute an appropriate baseline for validating GO similarity. Secondly, we introduce GraSM, a novel method that uses all the information in the graph structure of the Gene Ontology, instead of considering it as a hierarchical tree. GraSM gives a consistently higher family similarity correlation on all aspects of GO than the original semantic similarity measures.
Hierarchical organization in complex networks.
(2003)

Many real networks in nature and society share two generic properties: they are scale-free and they display a high degree of clustering. We show that these two features are the consequence of a hierarchical organization, implying that small groups of nodes organize in a hierarchical manner into increasingly large groups, while maintaining a scale-free topology. In hierarchical networks, the degree of clustering characterizing the different groups follows a strict scaling law, which can be used to identify the presence of a hierarchical organization in real networks. We find that several real networks, such as the Worldwideweb, actor network, the Internet at the domain level, and the semantic web obey this scaling law, indicating that hierarchy is a fundamental characteristic of many complex systems.
Lest We Remember: Cold Boot Attacks on Encryption Keys
(2008)

Contrary to widespread assumption, dynamic RAM (DRAM), the main memory in most modern computers, retains its contents for several seconds after power is lost, even at room temperature and even if removed from a motherboard. Although DRAM becomes less reliable when it is not refreshed, it is not immediately erased, and its contents persist sufficiently for malicious (or forensic) acquisition of usable full-system memory images. We show that this phenomenon limits the ability of an operating system to protect cryptographic key material from an attacker with physical access to a machine. It poses a particular threat to laptop users who rely on disk encryption: we demonstrate that it could be used to compromise several popular disk encryption products without the need for any special devices or materials. We experimentally characterize the extent and predictability of memory retention and report that remanence times can be increased dramatically with simple cooling techniques. We offer new algorithms for finding cryptographic keys in memory images and for correcting errors caused by bit decay. Though we discuss several strategies for mitigating these risks, we know of no simple remedy that would eliminate them.
Object Detection with Discriminatively Trained Part-Based Models
(2014)

• Lighting. When an object is in bright light, it looks brighter than when it’s in shadow, so a program can’t just look at image intensity values. • Within-class variation. Different instances of the same kind of object can look quite different to one another. For example, a green station wagon and a red convertible are both cars, so a program can’t simply compare a picture to one example. • Aspect. The same object can look very different when viewed at from different directions—pick up a book and compare its cover and its spine to see this effect. Again, this means that a program might need to have many examples of each type of object. • Deformation. Many objects can change their appearance significantly without their identity changing. For example, you can move your limbs around, change clothes, paint your face, or have your hair cut. You will look very different indeed, but you will still be a person.
Simultaneous Detection and Segmentation
(2014)

We aim to detect all instances of a category in an image and, for each instance, mark the pixels that belong to it. We call this task Simultaneous Detection and Segmentation (SDS). Unlike classical bounding box detection, SDS requires a segmentation and not just a box. Unlike classical semantic segmentation, we require individual object instances. We build on recent work that uses convolutional neural networks to classify category-independent region proposals (R-CNN [16]), introducing a novel architecture tailored for SDS. We then use category-specific, topdown figure-ground predictions to refine our bottom-up proposals. We show a 7 point boost (16% relative) over our baselines on SDS, a 5 point boost (10% relative) over state-of-the-art on semantic segmentation, and state-of-the-art performance in object detection. Finally, we provide diagnostic tools that unpack performance and provide directions for future work.
Applications of soft union sets to hemirings via SU-h-ideals
(2014)

The aim of this article is to lay a foundation for providing a soft algebraic tool in considering many problems that contain uncertainties. In order to provide these soft algebraic structures, we introduce the concepts of soft union hemirings (soft union h-ideals) of hemirings by soft intersection-union product and obtain some related results. Finally, we investigate some characterizations of h-hemiregular hemirings by soft union h-ideals.
Effects of an intervention to increase bed alarm use to prevent falls in hospitalized patients: a cluster randomized trial.
(2012)

BACKGROUND
Bed alarm systems intended to prevent hospital falls have not been formally evaluated.


OBJECTIVE
To investigate whether an intervention aimed at increasing bed alarm use decreases hospital falls and related events.


DESIGN
Pair-matched, cluster randomized trial over 18 months. Nursing units were allocated by computer-generated randomization on the basis of baseline fall rates. Patients and outcome assessors were blinded to unit assignment; outcome assessors may have become unblinded. (ClinicalTrials.gov registration number: NCT00183053)


SETTING
16 nursing units in an urban community hospital.


PATIENTS
27 672 inpatients in general medical, surgical, and specialty units.


INTERVENTION
Education, training, and technical support to promote use of a standard bed alarm system (intervention units); bed alarms available but not formally promoted or supported (control units).


MEASUREMENTS
Pre-post difference in change in falls per 1000 patient-days (primary end point); number of patients who fell, fall-related injuries, and number of patients restrained (secondary end points).


RESULTS
Prevalence of alarm use was 64.41 days per 1000 patient-days on intervention units and 1.79 days per 1000 patient-days on control units (P = 0.004). There was no difference in change in fall rates per 1000 patient-days (risk ratio, 1.09 [95% CI, 0.85 to 1.53]; difference, 0.41 [CI, -1.05 to 2.47], which corresponds to a greater difference in falls in control vs. intervention units) or in the number of patients who fell, injurious fall rates, or the number of patients physically restrained on intervention units compared with control units.


LIMITATION
The study was conducted at a single site and was slightly underpowered compared with the initial design.


CONCLUSION
An intervention designed to increase bed alarm use in an urban hospital increased alarm use but had no statistically or clinically significant effect on fall-related events or physical restraint use.


PRIMARY FUNDING SOURCE
National Institute on Aging.
Design and control of a GaN-based, 13-level, flying capacitor multilevel inverter
(2016)

Multilevel topologies are an appealing method to achieve higher power density inverters for both mobile and stationary systems. This work discusses the design and development of a 13-level, flying capacitor multilevel (FCML) inverter. Operating from an 800 V bus, this inverter requires switches with a voltage blocking capability of less than 80 V. A 120 kHz switching frequency is enabled through the use of GaN FETs and the development of custom integrated switching cells, which reduce commutation loop inductance and allow for a modular design. Additionally, the frequency multiplication effect of FCML inverters allows the output inductor of the inverter to be made exceptionally small (4.7 μH) while maintaining a 0.7 % THD due to the 1.44 MHz effective inductor ripple frequency.